Handbook of Artificial Intelligence and Machine Learning in Decision Making
Description
This volume presents a collection of invited chapters covering a broad range of perspectives on AI and decision-making. The scope is broad, and the potential impact is expected to be broader. Therefore, this volume represents only the beginning of a timely exploration of decision-making processes across thousands of applications that AI is expected to influence, including engineering, healthcare, management, human behavior, and business.
This handbook includes several applications of decision-making based on artificial intelligence and machine learning techniques. This book also explores both new methods and well-established techniques in several topics related to AI and decision-making.
This book is suitable for practitioners and researchers interested in artificial intelligence, machine learning, decision-making, and related topics.
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Persons
Prof. Daras holds a Bachelor in in Mathematics, Department of Mathematics, University of Athens and Diplôme d'Etudes Approfondies (D.E.A.), Département des Mathématiques, Université des Sciences et Techniques de Lille Flandres-Artois, Lille. He earned his Ph.D. from the Département des Mathématiques, Université des Sciences et Techniques de Lille Flandres-Artois, Lille (Supervisors: C. Brezinski, G. Couré), with the highest distinction of French Universities. He is a Scientific Associate with the Technical University of Crete, Greece, and a full Professor of Pure and Applied Mathematics at the Department of Mathematics and Engineering Sciences, Hellenic Military Academy (HMA) and at the School of Telecommunications of Electronic Transmission Officers, Greece. He was the Dean at the HMA, and the Organizer and President of 7 International Scientific Conferences. He is currently the Director of two Master's Programs in Cryptography and in Operations Research and Decision Making. His research interests include Numerical Analysis, Complex Analysis, High-Dimensional Data Analysis, Cryptography, Operational Research, Military Operations Research, Optimization, and Application of Mathematics in Combat Models and Mathematical Modeling for Engineering Systems. He has authored more than 50 papers and studies in academic journals and conferences. He has published 9 edited volumes and 5 special journal issues (among others: "Applications of Mathematics and Informatics in Military Science" (from Springer), "Cryptography and its Applications in the Armed Forces", "Mathematics and Informatics in Military Science", "Operations Research, Engineering, and Cyber Security - Trends in Applied Mathematics" (from Springer), "Cyber-Security and Information Warfare", "Analysis, Cryptography and Information Science", "Approximation and Computation in Science and Engineering" (from Springer), "Applications of Mathematics and Informatics in Science and Engineering" (from Springer), "Computational Mathematics and Variational Analysis" (from Springer), "Computation, Cryptography and Network Security" (from Springer), "Military Logistics: Research Advances and Future Trends" (from Springer), "Modern Discrete Mathematics and Analysis with Applications in Cryptography Information Systems and Modeling" (from Springer)). Prof. Daras is a member of the Hellenic Mathematical Society, Hellenic Operational Research Society. He has been awarded one of the awards given by the Academy of Athens for scientific publications in Mathematics.
Antonios Fytopoulos graduated from the Hellenic Army Academy as an officer and pursued a military career, where he received numerous awards. In 2018 he received his diploma from the School of Chemical Engineering of the National Technical University of Athens, where he graduated in the top 5% of his class. In 2017 he joined KU Leuven as a Ph.D. candidate in the Department of Chemical Engineering. His Ph.D. project focused on population balance-based optimization of deracemization processes for pharmaceutical applications. He has participated and presented his research at several national and international conferences and coauthored articles in international peer-reviewed journals.Panos Pardalos was born in Greece and graduated from Athens University (Department of Mathematics). He received his PhD (Computes and Information Sciences) from the University of Minnesota. He is a Distinguished Emeritus Professor in the Department of Industrial and Systems Engineering at the University of Florida, and an affiliated faculty of Biomedical Engineering and Computer Science & Information & Engineering departments.
Panos Pardalos is a world-renowned leader in Global Optimization, Mathematical Modeling, Energy Systems, Financial applications, and Data Sciences. He is a Fellow of AAAS, AAIA, AIMBE, EUROPT, and INFORMS and was awarded the 2013 Constantin Caratheodory Prize of the International Society of Global Optimization. In addition, Panos Pardalos has been awarded the 2013 EURO Gold Medal prize bestowed by the Association for European Operational Research Societies. This medal is the preeminent European award given to Operations Research (OR) professionals for "scientific contributions that stand the test of time."
Panos Pardalos has been awarded a prestigious Humboldt Research Award (2018-2019). The Humboldt Research Award is granted in recognition of a researcher's entire achievements to date - fundamental discoveries, new theories, insights that have had significant impact on their discipline.
Panos Pardalos is also a Member of several Academies of Sciences, and he holds several honorary PhD degrees and affiliations. He is the Founding Editor of Optimization Letters, Energy Systems, and Co-Founder of the International Journal of Global Optimization, Computational Management Science, and Springer Nature Operations Research Forum. He has published over 600 journal papers, and edited/authored over 200 books. He is one of the most cited authors and has graduated 71 PhD students so far.
Content
Do SDGs Support Human Security? A Machine Learning Analysis with Policy Recommendations.- Which AI/ML Techniques to Select for Applications to Decision Making: Towards Theoretical Explanations of Empirical Discoveries.- Crafting & Upskilling Human Decision-Making Capabilities through 3 Transformations in an era of Artificial Intelligence.- An Overview of Reinforcement Learning Algorithms for Causal Discovery.- Maximizing influence in competitive social networks via LLM and in-context learning.- Decisions based on choice models and their applications.- Navigating Digital Discretion: Soft AI, Public Values, and Empirical Insights from Social Work.- Representation of unconscious activity of human brain in decision making and artificial intelligence.- Software solutions using neural networks for monitoring natural processes.- Strategies in Healthcare Management: A Review of Efficiency, Technology, and Patient-Centered Practices.- Artificial Intelligence as a Tool for Decision Making in Healthcare.- AI-augmented decision-making in family business.